MétaCan
Menu
Back to cohort
Record W7000275846

¿Es necesaria la prueba de inclinación en pacientes con diagnóstico clínico de síncope vasovagal?: Resultados utilizando un protocolo no sensibilizado

2011· article· es· W7000275846 on OpenAlexaboutno aff

Bibliographic record

Venuenot available
Typearticle
Languagees
FieldMedicine
TopicCardiovascular Syncope and Autonomic Disorders
Canadian institutionsnot available
Fundersnot available
KeywordsMedical screeningPredictive valueStatistical analysis
DOInot available

Abstract

fetched live from OpenAlex

Introducción:La prueba de inclinación es un estudio no invasivo, sencillo y de bajo riesgo, donde la utilización de protocolos no sensibilizados sirven para acortar los tiempos de la prueba. Objetivo:Determinar en pacientes con síncope la utilidad de la prueba de inclinación no sensibilizada con fármacos y comparar los resultados con la probabilidad clínica pre-test. Métodos:Se incluyeron pacientes >15 años de edad, con síncope o presíncope, con clínica sugestiva de origen vasovagal, utilizando la escala de Calgary. Resultados:Se analizaron 70 pacientes; edad: 39 ± 20 años, 66% mujeres. De los pacientes, 94% presentó una puntuación >-1, pero sólo 30% de las pruebas fueron positivas. Una puntuación >-2 no se asoció con el resultado de la prueba. La mayoría de los pacientes presentaron una puntuación de 1 (52) y 2 (11), resultando en una prueba positiva en 32% y 9%, respectivamente. En pacientes con probabilidad pre-test baja, hubo mayor número de pruebas negativas (100% con una puntuación de -2 y 50% con puntuación de -5). Conclusiones:El estudio mostró que en pacientes con síncope vasovagal, sugerido por la evaluación clínica, la prueba de inclinación no sensibilizada no proporcionó información adicional, con un número significativo de falsos negativos.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.076
metaresearch head score (Gemma)0.141
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.076
Threshold uncertainty score0.400

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0760.141
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0030.002
Open science0.0010.002
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0030.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.015
GPT teacher head0.270
Teacher spread0.254 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations1
Published2011
Admission routes1
Has abstractyes

Explore more

Same topicCardiovascular Syncope and Autonomic DisordersFrench-language works237,207